Let’s call it like it is. Being in startups and better yet being a founder has been the hot ticket for a while now. A lot has been written about how to start a startup, even in biotech, but I want to put a different spin on it.

Should you REALLY be starting that startup?

Stay with me here and don’t close your browser window thinking I am overly cautious and sound like your parents. I did found a startup (Sample6) and it continues to be an exceptional journey. BUT let’s be real: the experience is going to suck and at the same time is going to be the single most rewarding professional adventure you’ve ever undertaken.

So why am I saying this? Because as early career technologists like undergrads, grads, postdocs, faculty, or as employees at larger companies, we often have an incredibly poor view into the challenges of commercialization a.k.a. what it takes to build a business. It’s all worth it but you have to be absolutely convinced that the reasons you do it are worth crossing the valley of death to achieve it.

Let me constrain that a little more. This is not a post about consumer web, mobile, or even big data (substitute any software-based startup). This is about hard tech. Is it snobbish to think of the degree of difficulty of getting a startup in software as “soft” and in hardtech/hardware as “hard”? I don’t think so, rather it reflects the fundamental differences in the distribution of hurdles. The hurdle of getting to a proof-of-concept in IT is low, while the hurdles of scaling are high. The hurdles in hard tech are high early on, while they may be lower later on i.e. once you have approval in that field you have exclusivity for a good while.

But since this is a biotech blog and, more specifically, because the focus is synthetic biology, let me lay out what I want to highlight here. This post is about choices we as founders make and in particular in this case because we’re in biotech, it’s about the initial underlying technology. I say “initial” because in a shameless adaptation of whichever military general said it first: “No technology survives initial contact with the real world”. What it takes to build a startup successfully into an actual company is a technology that is exceptional.

Now you may think whatever it is you’re working on is the next big thing since sliced bread, but trust me: it most likely is not. Do not fall into the trap of trying to shoehorn your Ph.D. project into a startup. The worst that could happen is that you actually get funding and now have to embark on the long and painful road of trying to prove out a technology improvement that the market doesn’t care about that much.

So yes I’ve rambled on and told you a few things about what you shouldn’t do… so what SHOULD you do? What makes for a compelling product-market fit? That’s the question you have to answer. In this case for us biotechnologists it’s very often related to what the performance parameters of a technology are, but importantly thinking about it from a customer’s point of view sometimes yields more valuable realizations.

In some particular hierarchy, let’s call it Mike’s Ladder of Technology Awesomeness™, which we can debate (tweet at me @mkoeris or leave a comment), here they are:

Enable a behavior or workflow that wasn’t possible previously.

This one ranks the highest in my list because it’s applicable to not just therapeutics, but also diagnostics, medical devices, and industrial biotechnology. In particular, the story of Amgen’s anemia drug Epogen (EPO) comes to mind here. For those unfamiliar, their initial target market was the comparatively small segment of dialysis patients with severe anemia. By giving them EPO, patients experienced a life-changing (and rapid!) improvement in their condition — like being able to get out of bed and having energy to participate in normal daily activities as opposed to being in a state of constant and debilitating fatigue. If your technology does that for your target customer market, which by the way doesn’t have to be big, then that’s a really good start.

This one may really underlie or power the enabling behavior, but it may also just be straight up improvement in performance. Now let me qualify that statement. The performance improvement has to be BIG! I am talking 10X or more. Why you may ask? Because it’s hard to build technology and it’s hard to get customers to adopt it. At least be an order of magnitude better such that you won’t have that particular debate with your customers. You’ll have to work hard to convince me that your 13.2% improvement is meaningful. Biology doesn’t work very linearly; it’s fundamentally more logarithmic / exponential.

An example, this time from industrial biology and really also a shameless plug is Sample6. Our test for bacterial pathogens doesn’t need enrichment, so we’re short-circuiting the test protocol. That means we’re enabling our target customers (food manufacturers) to test their environments for the presence of bacterial pathogens within the production shift. Currently they have to wait one to several days for results to come in. That’s a meaningful change and valuable behavior shift.

Cheaper

Plenty of people think that by making something 10X, or better yet, 100X cheaper, makes for a good business. I would argue differently because you’re not able to capture the margin as well as you think. First your product has to be comparable or identical if you want to charge the same, and then you’re STILL going to have to give up margin to your customers to get them to switch. That’s a hard business to be in and requires capital, a big team, and a long time horizon.

Having said that there is a huge amount of opportunity for good product-market fit, but you need to be rigorous, too, about finding those opportunities. They don’t come to you — and they aren’t obvious at first. Iterate quickly and fail fast! The lean startup methodology that has been adopted widely in consumer web/mobile applications, and it’s worthwhile to start thinking about how that can be applied to biotechnology. My colleagues James Taylor, Euan Ramsey and I wrote about it earlier trying to frame the lean startup methodology in the context of biotechnology.

Last word of warning: too often a budding (bio)technologist is making choices based on defaults.

Think hard about the maximal value of your technology for each customer segment. Once you are convinced that you have found it, go hard after it!

Then email me; I’d love to both chew on it and see if you can convince me!

In December of 2013, I was invited to give a presentation to a group of MD and PhD researchers at Sunnybrook Health Sciences Centre, which is one of the largest research hospitals in Canada. The is part of the Schulich Innovation Seminar series, and is intended to help researchers interested in commercializing their work. I was asked to provide an introduction to some of the financing, valuation and modelling issues faced by early-stage start-ups. The video and slide show can be viewed here

Couple of comments:

- The seminar series is led by Dr Brian Courtney, Dr Graham Wright and Dr Bradley Strauss. Dr Courtney, who introduced me, is a cardiologist and is also the founder and CEO of Colibri Technologies, which is developing a catheter imaging system for use in cardiac procedures. Dr Strauss is the division head of cardiology and is founder and chairman of Matrizyme, which is a clinical-stage biopharmaceutical company

- Some terms and comments are specific to Canada. A couple of times I reference the show “Dragon’s Den” which is a popular angel investing show on Canadian television. Also, the tax credits mentioned in the financial modelling slides are specific to Canada

- During the medtech modelling slides, I state that class II devices require a 510(k) for regulatory approval, however, the appropriate term is regulatory clearance

- On several occasions, I incorrectly state that Versant Ventures is based in Boston, when , in fact, its offices are based in California, Minneapolis, Basel and Vancouver

I have heard this cliché 2,189 times. That might not be an exact count, but it is within the ballpark

As someone who questions most things, I questioned this. I have met and observed many successful entrepreneurs, both in life sciences and other sectors. Although content, none of these people were joyful or ecstatic or over-the-moon about their ventures. In fact, most seemed stressed, concerned and overwhelmed. So, I wondered if the cliché was wrong. I also wondered whether, to succeed in spite of loving what you do, is to succeed at all. Something did not make sense

Besides entrepreneurs, I tend to hang around with a lot of young parents, which is probably a function of age. It was not until recently that I realized that the same pattern I observed of successful entrepreneurs was also in loving parents. They are unequivocally happy to have children, but are also often stressed, concerned and overwhelmed. From this, it occurred to me that my expectation that love had something to do with joy or ecstasy was a terrible miscalculation. Suddenly, it all made sense

I cannot prove the equation, but I think love comes in two parts. The first is sacrifice. The extent to which you love someone or something is the extent to which you will give up, trade off or do what is not in your easy interest. The second is vulnerability. To love is to risk loss because we do not concern ourselves with the things we do not care about. Combine the two, and to love is tough! It will wear down even the most Zenlike and mindful person. But love, in itself, is also tough! By that, I mean that it is an incredibly powerful and resilient force that helps us take on the greatest of challenges. Raising children is tough, starting a company is tough, but love is tougher

In closing, I would like to dedicate this post to the loving parents (especially my own), the loving entrepreneurs, and the lucky few who are both. To quote one of my favorite songs… the good love fight for, everyday!

Now in it’s second year, the startup conference focusing on Synthetic Biology or SynBio will be held in SF. Yours truly will be giving a short update talk but mostly it’s about the various constituents of the ecosystem: entrepreneurs, investors, service providers.

More below:

On November 15, 2013, SynBioBeta will once again be bringing together the synthetic biology community for the second annual SynBioBeta Conference at Mission Bay Conference Center UCSF.

The conference provides a venue for companies, both established and startups, investors and academics to meet, partner, exchange ideas and learn about the latest advances in the rapidly evolving field of synthetic biology. Some of the topics on the agenda are: Advances in Gene and Genome Synthesis, Scale-up in the Bioeconomy, SynBio Angel and VC Funding and more.

The conference will be followed by a cocktail reception Friday evening and on Saturday, November 16, 2013, SynBioBeta will be presenting a Networking Brunch Cruise for anyone in the synthetic biology community to attend. Register using promo code SBBIG3 to receive a 20% discount on the conference registration. For more information on the conference and the Brunch Cruise, please visit www.synbiobeta.com

I am happy to announce the first instalment of our BiotechStart Conversations. In these, I will be interviewing a wide range of biotechnology entrepreneurs with the aim of understanding how others are bringing cutting edge technologies to market, financing their companies, and building their organizations. This is a conversation by biotech-entrepreneurs for biotech-entrepreneurs.

In our first interview, I am speaking with Mike Koeris. Mike is a co-founder of BiotechStart by night and co-founder of Sample6 Technologies by day. Enjoy, it was a great time talking shop with Mike.

“Co-founder equity” brings to mind a small group of entrepreneurs huddled in a basement, feverishly working days, nights and weekends to launch a start-up. There are a number of prominent life sciences companies that sprung from humble beginnings (i.e. Boston Scientific, Arthrex), although, for the most part, venture capitalists seem to be moving away from “funding start-ups” and towards “founding start-ups.” Regardless, for those interested in how to fairly divide equity with co-founders, this article may be of value.

Before I begin, I figured I would list three rules that supersede the mostly legal and mathematical exercise of allocating shares among co-founders.

Rule #1: You need co-founders (at least one)

Although I am not a professional venture investor, I would never invest in a start-up with a single co-founder. More important than the complement of skills that a co-founder can offer, every entrepreneur needs someone with them “in the trenches.” Without veering too far into the world of positive psychology, there is enough evidence to suggest that people are better equipped to handle stressful situations when they have strong social support.

Rule #2: You need co-founders that you can trust

In my observation, trust among co-founders results from starting a venture for the same reasons that are the right reasons. Trust takes time to observe and develop, and therefore, the best co-founding teams tend to have a pre-existing relationship.

Rule #3: Focus on maximizing the pie, not the pieces

Once the equity is divided, there should be consensus that the intent is to maximize the overall valuation. ”If the company wins, everyone wins; if the company loses, everyone loses.” This philosophy prevails when there there is strong mutual trust among the co-founders.

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Returning to the how of the matter, I favor the following structure:

- All co-founders agree to restricted stock arrangements. A restricted stock is like a stock option in that it is subject to vesting (i.e. it is not earned immediately), but, the price to acquire the stock is nil or nominal

- As part of the restricted stock agreement, each co-founder must sign a contract, which contains a job description, as well the number of hours or range of hours per week the person is expected to work

- Contracts are structured over a two year period, renewable and reviewable quarterly. A contract may be terminated quarterly at the discretion of either the co-founder or the company. Restricted founder shares vest at the conclusion of each quarter. If a co-founder leaves the company, vested restricted shares may be subject to claw-back (e.g. 50%). Two years typically reflects the timeframe over which founders are working primarily for equity as the company is unlikely to have adequate cash flow to pay market wages

- The number of restricted founder shares vested quarterly is computed as the number of expected hours worked in the quarter multiplied by the imputed hourly rate of labor. For example, a senior person may be granted 100 shares per hour, whereas a less senior person may be granted 50 shares per hour

- The contracts are reviewable quarterly to allow for changes to be made to the job description, number of hours worked and the imputed rate of labor. Often, it is difficult to evaluate a person’s contributions at the out-set, and therefore, the contracts must be structured to accommodate change. However, overly frequent (i.e. monthly) renewal periods can be an administrative burden. Time sheets are also not required, as everyone should be operating on good faith

- The contracts do not preclude the co-founders from entering into employment or consulting agreements once the company has raised or generates sufficient cash flow. Vesting schedules are also subject to change in the event of a series A or seed round

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Once this is done, it is best to put together a cap table that summarizes the number of fully-vested shares belonging to the co-
founders as well as percentage of shares. I also like to add an option pool, as well as a seed and Series A round to estimate the co-founder’s interest in the near future years.

As per usual, I welcome any comments or questions people might have. In my observation, this system is both sufficiently simple and effective in that non-finance co-founders can understand the mechanics and appropriately focus on driving valuation

My last article identified issues with government incentive programs for life science generated some buzz. I received a number of comments and messages from readers ranging from total agreement to total disagreement. Just to reiterate, I believe the government has an important role to play in supporting the adoption of new technologies and companies, and there are examples of direct and indirect funding programs that help to achieve this in countries around the world. However, I am not sure that more money is necessarily the answer. I think there are less expensive ways to improve outcomes.

To briefly digress, the movie Moneyball was on television this week. For those that have not seen it, Moneyball retells the 2002 Major League Baseball season of the Oakland Athletics, and the challenge to field a winning team despite being a small market club with limited payroll. At one memorable point in the movie, Athletics manager Billy Beane, played by Brad Pitt, identifies his problem:

“The problem we’re trying to solve is that there are rich teams and there are poor teams. Then there’s fifty feet of crap, and then there’s us. It’s an unfair game…. we’ve got to think differently. “

Beane subsequently hires a sabermetrics analyst as his assistant, who uses baseball statistics and mathematical models to identify undervalued players. Although the decision is widely panned by others in the organization as radical, it proves successful, and the Athletics finish the season with a record of 103-59, punctuated by a 20 game win streak. Moneyballshows that what is lacked in capital, can be made up with intelligence.

I often feel like life sciences is the Oakland Athletics of the venture community in that it is woefully and undeservedly underfunded. However, I also feel that too much time is spent lamenting the lack of capital, and too little time is spent brainstorming alternatives. I believe there are two ways in which the community can become considerably “smarter”, aided by the government with little financial expenditure:

(1) Education programs on life science commercialization

The University of California San Francisco recently announced a 10 week course called the Lean LaunchPad for Life Sciences and Healthcare, to teach researchers how to commercialize technology developed in an academic setting. The course is of little cost to students, non-credit, and spearheaded by some venture heavyweights (notably Steve Blank). In my observation, many PhD students and post docs are genuinely curious about the commercialization process, but frustrated by the lack of education resources. Also, a stagnant industry means that many researchers are underemployed or underutilized and have time to learn. The proliferation of online and open course ware has resulted in powerful education economies of scale, and a government program to subsidize and deliver such an initiative would reach many students at relatively low cost. Although this would not result in an immediate upturn in life science ventures, the next generation would be better prepared for when the opportunity arrives

(2) Healthcare adoption programs

Healthcare is one of the few sectors in which the government also pays for the innovation it helps to fund. Historically, there has been a massive disconnect in the value chain, whereby those ministries or departments that oversee innovation have not been in dialogue with those that oversee the administration or delivery of healthcare. Going forward, the system needs to achieve some harmony between the push and pull of commercialization, whereas the push comes from the academic research, and the pull comes from the demands of the healthcare system. An interesting and local example of a program to achieve this is MaRS EXCITE, which is an interface between ventures, academic health researchers, and the Ontario government. The program helps pre-market devices and diagnostics perform the studies and gather the evidence required to receive regulatory and reimbursement approval, and gain assurance that they will be adopted by the healthcare system. The program is open to both start-ups and multinationals that pay for the studies performed by the academic health centers in the same way they would with a CRO. The incremental cost of MaRS EXCITE is marginal because they act as an interface. The commitment from the government is mostly non-financial, but helps to ensure that those start-ups that are funded are more likely to be successful.

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Neither program is a cure-all, a short-term solution, nor perfect substitute for direct and indirect funding support. However, whereas funding programs are meant to increase “I”, these are focused on increasing “ROI”. To reiterate, what is lacked in capital can be made up with intelligence.

I must admit that I was politically indifferent for most of my life, but there was a sharp and sudden change when I entered the world of life science start-ups. Government intervention impacts all stages of the life science value chain, from the funding of basic research, to the approval of new technologies, to the eventual reimbursement and delivery of health care. Some countries (like Canada, where I live) are also committed to supporting the life science ventures through a variety of direct (loan, grant, equity) and indirect (tax credits for investors or R&D) programs. Considerable ex post empirical attention is given to whether these initiatives are successful, but there seems to be little ex ante discussion of the inherent limitations.

In my opinion, there are three critical issues with government incentive programs for life science start-ups:

(i) Government programs cannot fix underlying business model issues

For many years, commercializing a life science start-up was about “does it work?”, but the current sentiment is “does it matter?” Long gone are the days of Amgen and Genentech when companies with exciting technologies can raise large amounts of money with reassurance of a pot of gold at the end of the rainbow. This change in circumstance has resulted in a change in business model, forcing ventures to be leaner, smarter and more focused, however, there still seem to be a number of misguided philosophies (e.g. “Silver Medal Companies”). Successful ventures make for successful government programs, and not vice-versa.

(ii) Undue focus on job creation

Political myopia is widely acknowledge, and as someone who has a number of friends in politics, I can confirm that 80% of their time and effort is spent on how to get elected, and the remaining 20% is spent on what to do when elected. A surrogate endpoint for political performance and support is job creation, because more jobs equal more votes. As a result, many direct life science incentives are unduly focused on short-term job creation, when they should be focused on holistic long-term “value creation”, which encompasses value accruing to investors, founders, researchers, patients and employees as a whole. Whereas the concept of a lean start-up and the zero person virtual biotech might be gaining industry support, it probably will not gain political support.

(iii) Bureaucracy

To quote a friend of mine in politics, “anyone who thinks government is the solution has not worked in government.” The life science venture community tends to move and evolve at a much faster pace than government administrators, and I have personally witnessed a number of start-ups held in limbo due to the bureaucratic process. Also, it doesn’t take a Russian oil tycoon to realize that, whenever government intersects with business, special interests are often unjustly enriched.

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Based on these comments, one might conclude that I am a libertarian, which is actually not the case. I believe that the government has an important role to play in fostering the massive positive externalities that result from the creation and success of life science ventures. Also, I believe strongly that it is of little value to identify a problem without suggesting a solution, so, my next article will outline some government initiatives that I feel of greater value than what currently exists.

As someone relatively new to life science start-ups, one of the biggest challenges I struggle with is distinguishing signal from noise. There is no shortage of offline and online information and advice about entrepreneurship and life sciences (including this blog and my contributions) and it can be very difficult to separate what is good (signal) from what is bad (noise). Whereas the good is constructive, the bad is destructive, meaning that it not only does not help, but it also hurts.

Although this is an evolving process, I have come up with a three rules for filtering signal from noise. I will explain the process, and then give you an example of how I try to apply it.

Rule #1: Life sciences entrepreneurship is unique

In my observation, the online and offline discussion of start-ups is dominated by information technology. Although some of it is relevant to life sciences (for example, the concept of a lean start-up originated from IT), I would argue that most of it is not. I could list countless reasons as to why, but I think it is best summed up as follows: “IT is trial and error, life sciences is error and trial.” So, any entrepreneurship advice that is not specific to life sciences should probably be deeply discounted.

Rule #2: Domain expertise matters

Life sciences covers a large landscape, and there are few, if any (including venture capitalists) that possess both depth and breadth when it comes to understanding drugs (pharma and biotech), diagnostics and devices. While someone who has spent their career commercializing small molecule drugs could provide better insight to laboratory developed tests than a complete outsider (see rule #1), their insights would be similarly limited relative to someone that has founded a genetic assay company. Some information and advice is applicable to the entire life science landscape, but not necessarily all.

Rule #3: This above all – reason rules!

All information and advice comes from people, and the first two rules are really intended to narrow those candidates that are best qualified. Even if a person is experienced, successful and can be trusted, what they say is only as good as their reason. I don’t pretend to be an epistemologist, but if someone can’t explain why something is the case, it probably is not the case, and to believe otherwise is ad hominem.

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To provide an example of this process, I recently read Valuation in Life Sciences. There are many books on the topic of valuation, but I chose this text given that it was specific to life sciences, and that this sector faces a number of valuation issues uncommon to others. When I first started reading the book, it was immediately apparent that the content was focused on drug development (both pharma and biotech) and was of less applicable to diagnostics and devices. The book discussed how to measure the accretion of value as a drug progresses through the regulatory process, which is less applicable to a device or diagnostic that generally faces a lower regulatory hurdle and a higher adoption hurdle. Finally, most of the material was based in mathematical finance, namely options analysis, and in my opinion, failed to properly acknowledge that much of valuations has to do with validating the assumptions underlying the model. Given my finance background, I am acutely aware of the “garbage-in, garbage-out” problem, but, for someone without, this book would have been much more noise than signal!

If the customer is always right, then why not make them an investor? This might seem like an obvious statement, but I think it has powerful implications for start-ups in the innovation space looking for capital. I have written before about a finance value chain, which is business lexicon for funding a company from start (i.e. seed capital) to finish (i.e. exit and/or positive operating cash flow). The finance value chain exists in parallel to the overall company value chain of how an idea becomes a product and eventually reaches a customer. The idea of engaging customers as early as possible has firmly planted roots in the ICT start-up space (see Minimum Viable Product), so, can it be similarly adapted to the life sciences space?

As most know, there are three buyers of devices, drugs and diagnostics, namely patients, payers and providers. Of those three, I would argue that providers, namely physicians, are the “de facto customers” as they hold the bulk of the decision-making power. The rise in specialized and sophisticated health care has also given rise to health illiteracy, so, patients tend to carry the least weight. Payers are certainly influential in that they determine reimbursement rates (i.e. price) but just because something is reimbursed, does not necessarily mean it will be adopted (i.e. quantity). Ultimately, it is physicians, alone and in concert, that perform procedures, prescribe medications and request diagnostic tests, so, they are the linchpin in the customer equation.

I came across the idea of raising a seed round from physicians a couple of years ago when I saw a video about a Toronto-based start-up commercializing a prognostic assay for age-related macular degeneration. At about the 13 minute mark, the CEO discusses how the company was able to raise money from a group of ophthalmologists presented with the technology. At the time I first watched the video, I was “very new” to life sciences (as opposed to now, when I am just “new”), so, at the time I did not quite grasp the value of this approach. Over time, I have come to believe that this is a promising but uncommonly explored avenue for start-ups looking to raise a seed round.

As part of my research, I have put together a list of the pros and cons of MDs as Angel Investors. I welcome any comments and additions readers have.

PROS:

- Established MDs tend to be high net worth individuals and would qualify as accredited investors. They have stable and predictable incomes, and can allocate a portion of their portfolio to start-ups

- Medicine is becoming increasingly specialized and segmented. Specialists are able to understand the science underlying the business, as well as factors such as adoption, standard of care and work flow that drives their decision as eventual customers

- Doctors provide important and unparalleled non-financial capital, namely credibility, insights and connections. Not only is this valuable to the start-up, but it also means better expected risk-adjusted returns for them as investors

- Although a group of MDs is unlikely to fund large rounds (i.e. seven figures and above), they serve as an important signal to investors looking to syndicate or provide follow-on funding

- There are horror stories of angel investors squashed by venture capitals in follow-on rounds via down rounds, liquidation preferences, etc. By virtue of their position as customers, MDs as investors mitigate this risk

CONS:

- There is an acknowledged lack of later-stage life science funding, so, many angel investors are hesitant to participant in a seed round if there is little prospect of a Series A

- Recruiting and managing one large investor is considerably less challenging than managing a large group of small investors

- MDs are generally not seasoned start-up professionals and may feel overwhelmed by some of the business aspects of the science, such as valuation, intellectual property, regulatory, reimbursement, etc. Also, some might expect “halo deals” (i.e. 100X+) that occur in ICT but not life sciences

- For a platform technology with multiple indications, it may be difficult to identify the group of specialists best suited to investing. Also, investment from a group of specialists related to one indication may make it difficult to pivot to another if need be

- MDs using a new technology in which they have also invested may be perceived as a conflict of interest. Generally, this can be avoided by raising money from practitioners other than those on your Clinical Advisory Board and likely early adopters . (Being in Canada, an advantage is that the United States and Europe are often targeted as initial markets, and therefore, domestic MD investors are not the first users)

- MDs are busy people and are constantly being pitched by big pharma, biotech and medtech. It can be difficult to breach that barrier of being seen as just another “sales rep”